Synergic Use of Multi-Sensor Satellite Data for Volcanic Hazards Monitoring: The Fogo (Cape Verde) 2014–2015 Effusive Eruption

Monitoring volcanic eruptions provides key information for hazard assessment and its time evolution. Satellite remote sensing data are nowadays essential to perform such task, thanks to their capability to survey disastrous events also in remote and under-monitored regions, with frequent revisit time and accurate spatial resolution. Even though satellite imageries are presently used to analyze several phenomena related to eruptions, automatic methods and synergic exploitation of different sensors are rarely considered. In this work, we have analyzed satellite images coming from both synthetic apertureradar(SAR)andopticalsensors,tostudytheeffusiveeruptionofFogovolcano, CapeVerde,whichtookplacebetweenNovember2014andJanuary2015.Inparticular, we have exploited multi-sensor images from Sentinel-1, COSMO-SkyMed, Landsat8, and Earth-Observing-1 missions, to retrieve lava flow patterns and volcanic source parameters related to the eruption. The main outcome of our work is the application of a new automatic change detection technique for estimating the lava field and its temporalevolution,combiningtheSARintensityandtheinterferometricSARcoherence. The innovative algorithm is able to take full advantage of the Sentinel-1 mission’s 6day repeat cycle. Such data are here used for the first time for lava mapping, thereby providing an unprecedented example of using the multi-temporal interferometric SAR (InSAR) coherence to automatically monitor lava flow evolution in emergency phase. This new technique, jointly used with optical satellite images, is capable of resolving with spatial and temporal detail the evolution of lava flows. We have also performed differential SAR interferometry (DInSAR) to map the ground deformation and retrieve the feeding dyke by inverting syn-eruptive signals. Results from source modeling show a SW-NE oriented dyke, located inside Chã das Caldeiras, SW of the Pico do Fogo. Our work highlights how multidisciplinary and satellite open data, along with innovative and automatic processing techniques, may be adopted for real-time hazard estimates in an operational environment